Interaction of early environment, gender and genes of monoamine neurotransmission in the aetiology of depression in a large population-based Finnish birth cohort.

Abstract

Objectives Depression is a worldwide leading cause of morbidity and disability. Genetic studies have recently begun to elucidate its molecular aetiology. The authors investigated candidate genes of monoamine neurotransmission and early environmental risk factors for depressiveness in the genetically isolated population-based Northern Finland Birth Cohort 1966 (12 058 live births). Design The authors ascertained and subdivided the study sample (n=5225) based on measures of early development and of social environment, and examined candidate genes of monoamine neurotransmission, many of which have shown prior evidence of a gene-environment interaction for affective disorders, namely SLC6A4, TPH2, COMT, MAOA and the dopamine receptor genes DRD1-DRD5. Results and conclusion The authors observed no major genetic effects of the analysed variants on depressiveness. However, when measures of early development and of social environment were considered, some evidence of interaction was observed. Allelic variants of COMT interacted with high early developmental risk (p=0.005 for rs2239393 and p=0.02 for rs4680) so that the association with depression was detected only in individuals at high developmental risk group (p=0.0046 and β=0.056 for rs5993883-rs2239393-rs4680 risk haplotype CGG including Val158), particularly in males (p=0.0053 and β=0.083 for the haplotype CGG). Rs4274224 from DRD2 interacted with gender (p=0.017) showing a significant association with depressiveness in males (p=0.0006 and β=0.0023; p=0.00005 and β=0.069 for rs4648318-rs4274224 haplotype GG). The results support the role of genes of monoamine neurotransmission in the aetiology of depression conditional on environmental risk and sex, but not direct major effects of monoaminergic genes in this unselected population.

Full text

Page 1

Interaction of early environment, gender
and genes of monoamine
neurotransmission in the aetiology of
depression in a large population-based
Finnish birth cohort
Emma S Nyman,1,2,3Sonja Sulkava,1,2,4Pia Soronen,1,2Jouko Miettunen,5,6
Anu Loukola,1,2Virpi Leppa ¨,1,2,3Matti Joukamaa,7,8Pirjo Ma ¨ki,5
Marjo-Riitta Ja ¨rvelin,9,10,11Nelson Freimer,12Leena Peltonen,1,2,3,13,14
Juha Veijola,5,6Tiina Paunio1,2,4
ABSTRACT
Objectives: Depression is a worldwide leading cause
of morbidity and disability. Genetic studies have
recently begun to elucidate its molecular aetiology. The
authors investigated candidate genes of monoamine
neurotransmission and early environmental risk
factors for depressiveness in the genetically isolated
population-based Northern Finland Birth Cohort 1966
(12058 live births).
Design: The authors ascertained and subdivided the
study sample (n¼5225) based on measures of early
development and of social environment, and examined
candidate genes of monoamine neurotransmission,
many of which have shown prior evidence of
a geneeenvironment interaction for affective
disorders, namely SLC6A4, TPH2, COMT, MAOA and
the dopamine receptor genes DRD1eDRD5.
Results and conclusion: The authors observed no
major genetic effects of the analysed variants on
depressiveness. However, when measures of early
development and of social environment were
considered, some evidence of interaction was
observed. Allelic variants of COMT interacted with high
early developmental risk (p¼0.005 for rs2239393 and
p¼0.02 for rs4680) so that the association with
depression was detected only in individuals at high
developmental risk group (p¼0.0046 and b¼0.056 for
rs5993883ers2239393ers4680 risk haplotype CGG
including Val158), particularly in males (p¼0.0053 and
b¼0.083 for the haplotype CGG). Rs4274224 from
DRD2 interacted with gender (p¼0.017) showing
a significant association with depressiveness in males
(p¼0.0006 and b¼0.0023; p¼0.00005 and b¼0.069
for rs4648318ers4274224 haplotype GG). The results
support the role of genes of monoamine
neurotransmission in the aetiology of depression
conditional on environmental risk and sex, but not
direct major effects of monoaminergic genes in this
unselected population.
INTRODUCTION
Depression is a major cause of morbidity
worldwide, with major depression affecting
5e7% of the population annually and 16%
over a lifetime.1Although a genetic compo-
nent in the aetiology of major depression is
evident with a 40e50% heritability,2the
predisposing genetic background has so far
remained largely undefined, and recent
findingsfromgenome-wide
studies also point to a complex underlying
architecture.3Depressed patients frequently
exhibit comorbidities such as anxiety and
alcohol abuse,4
and
types5e7have been associated with depres-
sion proneness.
association
certainpersonality
ARTICLE SUMMARY
Article focus
- Impact
candidate genes with prior evidence of genee
environment interaction for affective disorders,
and of dopamine receptor genes.
- Geneeenvironment and geneegender interac-
tions in the aetiology of depression.
- Effect of measures of early development and of
social environment on depression.
on depressionofmonoaminergic
Key messages
- Genes of monoamine neurotransmission play
a role in the aetiology of depression conditional
on environmental risk, especially in males and in
individuals at high early developmental risk group;
in particular, there is evidence of an interaction
with a COMT high-risk haplotype including Val158.
- Gender-specific mechanisms and responses to
environmental effectors are evident in the
regulation of mood.
To cite: Nyman ES, Sulkava
S, Soronen P, et al.
Interaction of early
environment, gender and
genes of monoamine
neurotransmission in the
aetiology of depression in
a large population-based
Finnish birth cohort.
BMJ Open 2011;1:e000087.
doi:10.1136/bmjopen-2011-
000087
<Prepublication history and
additional figures for this
paper are available online. To
view these files please visit
the journal online (http://
bmjopen.bmj.com).
Received 31 January 2011
Accepted 27 June 2011
This final article is available
for use under the terms of
the Creative Commons
Attribution Non-Commercial
2.0 Licence; see
http://bmjopen.bmj.com
For numbered affiliations see
end of article.
Correspondence to
Dr Tiina Paunio;
tiina.paunio@thl.fi
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
1
Open AccessResearch

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Environmental risk factors, in particular stressors
influencing during development,8are considered to
have a significant impact on the development and course
of depression. It is likely that many of the genetic risk
factors for depression interact with the early develop-
mental environment, but recapture of these interactions
has remained a challenge for aetiological studies of
depression. Although the interplay between genes and
environment has been investigated with respect to
several psychiatric disorders9 10including depression,
this vast subject still remains largely unexplored. On the
other hand, addressing the effects of genes and envi-
ronment on psychiatric morbidity enables us to examine
the two main constituents in their aetiology. Therefore,
we wanted to include the environmental dimension in
our study in order also to explore geneeenvironment
interactions (G3E).
According to the monoamine hypothesis, depression is
caused by underactivity in brain monoamines, such as
dopamine, serotonin and norepinephrine.11Recent
results of neuroimaging studies have provided further
support for this theory.12The most solid evidence from
candidate gene studies has perhaps been obtained for
the interaction of the SLC6A4 gene for serotonin trans-
porter and stressful early and current life events,13
including positive results from a recent review14and
meta-analysis of all studies to date,15although there are
also
findings have been obtained on the COMT gene for
catechol-O-methyltransferase, an enzyme catabolising
catecholamines such as dopamine and norepinephrine,
which has been implicated in depression in conjunction
with stress,17and on the MAOA gene for monoamine
oxidase A, an enzyme-oxidising neurotransmitter and
dietary monoamines such as serotonin, norepinephrine
and dopamine, which has been associated with depres-
sion in interaction with severity of maltreatment in
childhood.17Furthermore, the TPH2 gene for trypto-
phan hydroxylase 2, which is the brain-specific form of
the key enzyme in serotonin synthesis, has been impli-
cated to interact with stress on disorders of cognitive
control and emotional regulation, including depres-
sion.18Within the dopamine transmission, the DRD2
gene for dopamine receptor D2 has been associated with
depressiveness and anxiety, combined with an effect of
parenting in childhood,19and the DRD4 gene for
dopamine receptor D4 has been associated with an
increased risk for obesity in women with seasonal affec-
tive disorder.20
Thus, genes from the monoamine
neurotransmission system are among the most thor-
oughly studied in psychiatric genetics and in particular
in the aetiology of mood disorders, and have provided
perhaps the most robust evidence so far for interaction
with various types of risk environments, including
childhood environment.
We chose to include these candidate genes of mono-
amine neurotransmission showing prior evidence of
geneeenvironmentinteraction,
TPH2, COMT, MAOA, as well as the dopamine receptor
genes DRD1eDRD5, in our study on the aetiology of
depression with a particular focus on their interaction
with available markers reflecting measures of early
development and of social environment. The study was
performed in a sample of 5225 individuals from a large
Finnish isolated population cohort. As gender is an
important confounder for depression and at least some
of the genetic liability is gender-specific,2we also exam-
ined geneegender interactions in this sample.
contradictingresults.16
Other robust genetic
including
SLC6A4,
METHODS
Setting
We utilised the genetically isolated Northern Finland
Birth Cohort (NFBC 1966) to investigate the effects of
candidate genes and environmental risk factors during
the development on depressiveness. We subdivided the
study sample based on measures of early development
arising from the fetal growth environment and neuro-
logical development during the first year of life
(measure of early development) as well as from the
family environment during pregnancy and early child-
hood (measure of social environment). We examined
interactions of these measures with candidate genes of
the monoamine neurotransmitter systems, which have
prior evidence of geneeenvironment interactions on
affective disorders, namely SLC6A4, TPH2, COMT, MAOA
and the dopamine receptor genes DRD1eDRD5.
ARTICLE SUMMARY
Strengths and limitations of this study
- Depression as defined does not necessarily imply clinical
diagnosis of major depression but is based on a self-report or
Hopkins Symptom Check List-25 score. Despite this, the
prevalence of depressed mood was in the same range as that in
earlier reports.
- There was a notable drop-out rate of about half of the original
cohort members.
- The choice of measures of early development and of social
environment was limited by the availability of variables
collected.
- Advantages include the availability of longitudinal follow-up
data starting antenatally, enabling inclusion of the environ-
mental dimension without recall bias.
- The cohort’s unique genetic structure with isolation and more
genetic homogeneity permits identification of genetic-risk loci
that may be missed when using more heterogeneous
populations.
- The subjects are representative of the population, with all
cohort members born in the same year and within a geograph-
ically defined area.
- The study sample’s size is sufficient for identifying genetic
variants of moderate impact.
- Both genders are represented in almost equal amounts; gender
differences exist in both depression and temperament traits
such as harm avoidance.
- As the sample is a 1-year birth cohort, genetic effects may be
isolated from the effects of ageing; some psychiatric traits such
as harm avoidance are age-dependent.
2
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
Early environment, gender and genes in depression

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Study subjects
The Northern Finland Birth Cohort 1966 (NFBC 1966)
is a longitudinal 1-year birth cohort from an unselected
population (N¼12058 live births) comprising inhabi-
tants of the two northernmost provinces of Finland.21
Data collection was begun during the antenatal period,
and follow-up studies were performed at the ages of 1, 14
and 31 years. The cohort study was approved by the
Ethical Committee of Oulu University Faculty of Medi-
cine, and written informed consent was obtained from
all participants.
In 1997, for the 31-year follow-up study22all alive
cohort members with a known address (N¼11540) were
sent a postal questionnaire surveying lifestyle, social
status and health (76% participated), including the
Hopkins Symptom Check List-25 (HSCL)23and items on
self-reported lifetime depression diagnosis (eg, ‘Has
your doctor ever diagnosed a depressive disorder?’).
Additionally, cohort members who lived in Northern
Finland or had moved to the Helsinki area (N¼8465)
were invited to a clinical examination (71% partici-
pated) with another questionnaire to be filled in later
and sent to the research group (61% participated).24It
included, among others, a validated Finnish translation
of Cloninger’s Temperament and Character Inventory
(TCI) questionnaire.25
Current depressive symptoms were assessed by the
HSCL questionnaire,26a 25-item shortened version of an
originally 90-item questionnaire. HSCL contains 13-item
depression and 10-item anxiety subscales assessing pres-
ence and intensity of depressive and anxiety symptoms
during the previous week. Answers are scored on a scale
from 1 (not bothered) to 4 (extremely bothered). The
HSCL total score is the sum of items divided by the
number of items answered. We used mainly HSCL total
score, as symptoms of depression and anxiety are known
to overlap significantly. In the post hoc analyses, in order
to better understand the original association signals, the
separate HSCL subscales for depressive and anxiety
symptoms were also taken into consideration. In addi-
tion to current depressive symptoms (HSCL score) and
lifetime (diagnosed) depression, we used the TCI
temperament trait Harm avoidance5e7and its subcom-
ponents as a measure of proneness to depression.
The subjects (n¼5225; 2509 males, 2716 females; 45%
of the 31 year follow-up study sample or 43% of the
original study sample) were divided into high- and low-
risk groups based on the available information reflecting
measures of early neurodevelopment and of social
environment (table 1). The markers for the measure of
high early developmental risk included (1) low birth
weight (<2500 g),21considered to reflect suboptimal
growth environment during fetal life and to increase risk
for somatic and psychiatric diseases such as depression
in adulthood;27(2) late motor development as reflected
by first standing later than at the age of 10 months;28and
(3) late development of speech, defined by no words at
the age of 1 year.28If two of these risk indicators were
present, the subject was classified as having experienced
a high-risk environment for early brain development.
The markers for the measure of high social risk envi-
ronment included the occurrence of two or more of the
following five indicators for high-risk social environment
during pregnancy and early childhood: (1) unwanted
pregnancy (rated by mothers of the cohort members at
the sixth or seventh month of pregnancy),29(2) low
socio-economic status, shown to be linked with depres-
sion in the offspring in earlier studies,30as defined by
father’s occupation at birth (no occupation, unskilled
worker, or farmer with area under cultivation under 8
hectares), (3) single parenthood at birth, (4) low level of
education of mother (less than 9 years of primary
school) and (5) low level of information retrieval by the
mother related to pregnancy and childcare. There was
no significant drop-out in either of the high-risk groups,
as 43% and 41% of the individuals of high early devel-
opmental and social risk groups, and 47% and 46% of
those of the respective low-risk groups, were available for
study.
Genotyping methods
We investigated genes relevant within the context of the
monoamine hypothesis of depression: SLC6A4, TPH2,
COMT, MAOA and the dopamine receptor genes
DRD1eDRD5 (table 2). The genotyping was performed
at the Broad Institute (Cambridge, MA) on the
HumanCNV370-duo chip (Illumina, San Diego, Cali-
fornia) platformaccording
instructions. The analysed SNPs included HapMap tag
SNPs (http://www.hapmap.org/index.html.en)
were relatively evenly spaced to cover the genes and
flanking regions.
to the manufacturer’s
and
Statistical analysis
LD structures were determined using HAPLOVIEW.
Interaction and association/correlation analyses using
linear and logistic regression with permutation were
performed using PLINK Software Package Version 1.04,
in a stepwise manner to maximise our ability to detect
associations and to minimise multiple testing. First,
analyses were primarily performed to identify genetic
risk variants for current depressive symptoms (HSCL
score) interacting with measures of early development
(G3EDev) and of social environment (G3ESoc). For
variants giving significant evidence of interaction, we
also performed analyses separately in subgroups at high
and low risk, respectively. As gender is an important
confounder for depression, and at least some of the
genetic liability is gender-specific,2we also examined
geneegender interactions (GxSex). For variants showing
significant evidence of geneegender interaction, we also
performed analyses separately in males and females. In
order to achieve a more complete view of the effects of
the examined genes on depressive symptoms in the
cohort, we also examined their influence on the gender-
adjusted HSCL score in the complete sample regardless
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
3
Early environment, gender and genes in depression

Page 4

of environmental effectors. Finally, we tested for genee
environment correlations (rGEDevand rGSoc) and asso-
ciations of the risk environments with the HSCL score
(PASW Statistics 18, linear regression model). Second,
haplotype analyses were performed when two SNPs
located at physically close vicinity had given association
signals of p<0.05 when analysed separately. Third,
genetic variants and haplotypes which had been identi-
fied in the previous analyses were analysed post hoc with
respect to HSCL subscales (depressive and anxiety
symptoms), depression diagnosis and TCI temperament
Harm avoidance. We report pointwise empirical p values
generated by PLINK’s max(T) permutation (10000
permutations) throughout the manuscript, and state
explicitly where corrected empirical p values are
reported. SNPswith HardyeWeinberg Equilibrium
p values <0.05 were excluded from all analyses.
RESULTS
Geneeenvironment and geneegender interaction and
association analyses in relation to the HSCL score
We examined the effects of nine candidate genes of
monoamine neurotransmission on current depressive
symptoms (HSCL score) in a longitudinal population-
based NFBC 1966 cohort. In particular, we searched for
evidence of interaction of variants in these genes with
two measures of early growth, one with indicators for
potentially disturbed neurobehavioural development
(measure of early development) and the other with
risk factors fromsocial
emotional development (measure of social environ-
ment). The results are presented in table 2 in which
nominal p values are reported.
Out of the 69 genetic variants examined, none gave
a statistically significant association signal with depres-
siveness or for an interaction with measures of early
development or of social environment, which would
survive correction for multiple testing. We observed
nominal evidence for association with the HSCL score
(p<0.05) in the complete sample in the cases of
rs1487275 in TPH2, (p¼0.049, b¼0.008), rs4646316 in
COMT (p¼0.026, b¼0.012), rs4274224 and rs4581480 in
environmentfornormal
DRD2 (p¼0.022, b¼0.011; and p¼0.009, b¼0.022,
respectively), andrs13106539
b¼?0.008). Three variants of COMT and one of DRD3
showed some evidence of interaction (p<0.05) with high
early developmental risk with respect to the HSCL score
(p¼0.028 for rs737866, p¼0.005 for rs2239393 and
p¼0.020 from rs4680 from COMT, and rs9825563,
p¼0.045 from DRD3). All of these were associated with
the HSCL score in individuals of the high-risk group
(p¼0.036, b¼0.0414 for rs737866; p¼0.008, b¼0.0440
for rs2239393; p¼0.042, b¼0.0320 for rs4680; and
p¼0.022, b¼?0.0396 for rs9825563, respectively). None
of the variants gave any evidence of interaction with the
measure of social environment in relation to the HSCL
score. Five of the genetic variants showed some evidence
of interaction with gender (p<0.05), including rs737866
and rs5993883 in COMT and rs4274224 in DRD2. Out of
these, only rs4274224 was associated at p<0.05 with one
of the genders (p¼0.0006, b¼0.023 in males). The
evidence for geneeenvironment correlations (rGE) was
observed only nominally about rs1906451 from TPH2
(p¼0.035),
rs9825563 from DRD3 (p¼0.028). Despite a priori
evidence for the role of the markers which indicate
a high developmental risk for psychiatric health and well-
being, namely low birth weight21 27and late motor or
verbal development,28there was no correlation between
these markers and the HSCL score in the present sample
(p¼0.131), whereas the social high-risk environment
correlated significantly with the score (p¼0.00001).
Although none of the association findings of these
primary analyses survived correction for multiple testing,
post hoc association analyses in gender groups led to
a finding close to statistical significance, even when
taking into account the amount of multiple testing
performed (p¼0.0006 for males with rs4274224 in
DRD2). Furthermore, as there was an accumulation of
association signals within two highly plausible candidate
genes, DRD2 and COMT, we proceeded to perform
haplotype analyses on these genes in order to better
characterise the allelic variants which yielded the
observed suggestiveassociations,
in
DRD5
(p¼0.044,
rs265973 from
DRD1
(p¼0.047) and
and toobtain
Table 1Composition of the study sample from the NFBC 1966
N
Hopkins
Symptom
Check List
score>1.75*
Depression
diagnosis
Measure of early
developmenty
Measure of social
environmentz
High-riskx
229 (9%)
193 (7%)
422 (8%)
Low-risknd{
186 (7%)
195 (7%)
381 (7%)
High-riskx
912 (36%)
1034 (38%)
1946 (37%)
Low-riskndx
23 (0.9%)
33 (1.2%)
56 (1.1%)
Males
Females
All
2509
2716
5225
169 (7%)
269 (10%)
438 (8%)
79 (3%)
136 (5%)
215 (4%)
2094 (83%)
2328 (86%)
4422 (85%)
1574 (63%)
1649 (61%)
3223 (62%)
*There is prior support for using the Hopkins Symptom Check List score 1.75 as a cut-off when aiming to identify clinical depression.
yDefined by the presence of two out of three possible indicators for high early developmental risk: low birth weight, late motor development and
late development of speech.
zDefined by the presence of two out of five possible indicators for high social risk environment: unwanted pregnancy, low socio-economic
status, single parenthood, low level of education of mother and low activity for information retrieval by the mother. For further details, see text.
xBoth high early developmental and social risk present in 92 males (3,6%) and 67 females (2,4%).
{Not defined.
4
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
Early environment, gender and genes in depression

Page 5

Table 2
Interaction (G3E) and correlation (rGE) between genetic variants of genes of monoamine neurotransmission and measures of early development (G3EDev, rGEDev)*
and of social environment (G3ESoc, rGSoc)y and gender (G3Sex) on current depressive symptoms (Hopkins Symptom Check List score), and genetic association with
Hopkins Symptom Check List score in the complete study sample from the NFBC 1966 (All)
Gene
Gene name
Chromosome
SNP
Position/
bp
Minor
allele
MAFz
P (G3EDev)
P (G3ESoc)
P (G3sex)
P (All)
P (rGEDev)
P (rGSoc)
SLC6A4
Serotonin
transporter
17
rs1906451
25539605
G
0.44
0.608
0.363
0.784
0.268
0.747
0.035
rs3794808
25555919
A
0.41
0.365
0.263
0.799
0.320
0.402
0.064
rs140700
25567515
A
0.09
0.133
0.460
0.037xx
0.876
0.209
0.614
rs2066713
25575791
A
0.46
0.253
0.499
0.505
0.550
0.778
0.092
rs8071667
25576899
A
0.15
0.473
0.682
0.122
0.606
0.961
0.827
TPH2
Tryptophan
hydroxylase 2
12
rs4131348
70610746
G
0.12
0.844
0.937
0.400
0.497
0.705
0.241
rs2129575
70626340
A
0.22
0.787
0.682
0.432
0.423
0.173
0.298
rs1386496
70637057
G
0.16
0.983
0.404
0.293
0.792
0.837
0.226
rs2171363
70646531
A
0.43
0.762
0.983
0.016xx
0.814
0.692
0.940
rs10506645
70671767
A
0.23
0.996
0.756
0.102
0.789
0.888
0.721
rs1386497
70678557
C
0.17
0.816
0.131
0.452
0.797
0.640
0.172
rs1487276
70691326
A
0.21
0.888
0.088
0.838
0.908
0.591
0.219
rs9325202
70693744
A
0.48
0.805
0.074
0.488
0.473
0.913
0.675
rs1487275
70696559
C
0.37
0.972
0.054
0.625
0.049***
0.861
0.638
rs1386483
70698761
A
0.47
0.574
0.090
0.326
0.437
0.294
0.625
rs1872824
70716581
A
0.35
0.652
0.121
0.211
0.494
0.772
0.331
COMT
Catechol-O-
methyltransferase
22
rs6518591
18304021
G
0.16
0.688
0.255
0.919
0.303
0.150
0.385
rs737866
18310109
G
0.18
0.028x
0.853
0.024xx
0.755
0.623
0.489
rs1544325
18311668
G
0.48
0.318
0.376
0.192
0.822
0.999
0.931
rs174675
18314051
A
0.29
0.465
0.278
0.580
0.958
0.724
0.532
rs5993883
18317638
C
0.36
0.230
0.495
0.025xx
0.920
0.363
0.219
rs2239393
18330428
G
0.31
0.005{
0.765
0.256
0.930
0.838
0.459
rs4680
18331271
G
0.45
0.020**
0.956
0.501
0.346
0.412
0.498
rs4646316
18332132
A
0.18
0.205
0.165
0.933
0.026yyy
0.521
0.392
rs165774
18332561
A
0.25
0.081
0.516
0.089
0.215
0.538
0.239
rs165815
18339473
G
0.20
0.537
0.309
0.431
0.281
0.338
0.158
rs887199
18341955
A
0.20
0.544
0.325
0.401
0.306
0.314
0.168
rs2239395
18342203
C
0.02
0.144
0.655
0.153
0.390
0.224
0.664
Continued
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
5
Early environment, gender and genes in depression

Page 6

Table 2
Continued
Gene
Gene name
Chromosome
SNP
Position/
bp
Minor
allele
MAFz
P (G3EDev)
P (G3ESoc)
P (G3sex)
P (All)
P (rGEDev)
P (rGSoc)
MAOA
Monoamine
oxidase A
X
rs909525
43438146
G
0.45
0.559
0.871
0.554
0.165
0.255
0.932
rs12843268
43458610
A
0.40
0.271
0.837
0.266
0.103
0.052
0.932
rs6610845
43472954
G
0.41
0.232
0.795
0.263
0.170
0.060
0.524
rs3027409
43491977
C
0.02
0.748
0.928
0.950
0.194
0.703
0.068
rs6609257
43497652
G
0.50
0.848
0.320
0.470
0.077
0.075
0.898
rs3027415
43499385
G
0.18
0.218
0.550
0.905
0.613
0.105
0.408
DRD1
Dopamine
receptor D1
5
rs265973
174793305
G
0.50
0.529
0.614
0.549
0.888
0.047
0.831
rs265974
174793846
G
0.35
0.391
0.612
0.912
0.659
0.066
0.859
rs265976
174795026
A
0.23
0.578
0.707
0.915
0.826
0.077
0.933
rs5326
174802802
A
0.19
0.615
0.886
0.852
0.588
0.273
0.197
DRD2
Dopamine
receptor D2
11
rs1800497
112776038
A
0.17
0.079
0.825
0.691
0.467
0.921
0.264
rs2242592
112784640
G
0.37
0.757
0.466
0.283
0.736
0.143
0.393
rs1076563
112801119
C
0.50
0.053
0.813
0.897
0.662
0.234
0.856
rs2471857
112803549
A
0.17
0.518
0.494
0.823
0.901
0.884
0.126
rs4620755
112814829
A
0.22
0.383
0.997
0.951
0.176
0.065
0.992
rs7125415
112815891
A
0.19
0.084
0.389
0.789
0.231
0.163
0.947
rs4648318
112818599
G
0.34
0.711
0.885
0.631
0.684
0.214
0.466
rs4274224
112824662
G
0.24
0.067
0.777
0.017{{
0.022zzz
0.536
0.766
rs4581480
112829684
G
0.07
0.184
0.521
0.210
0.009xxx
0.082
0.760
rs7131056
112834984
C
0.49
0.564
0.795
0.413
0.964
0.622
0.138
rs4938019
112846601
G
0.23
0.069
0.651
0.643
0.584
0.320
0.059
rs12364283
112852165
G
0.08
0.280
0.504
0.441
0.861
0.633
0.804
rs10891556
112857971
A
0.24
0.076
0.519
0.638
0.589
0.380
0.052
rs6589377
112860946
G
0.17
0.286
0.617
0.061
0.552
0.502
0.915
DRD3
Dopamine
receptor D3
3
rs2087017
115324703
G
0.43
0.937
0.921
0.606
0.743
0.835
0.828
rs2134655
115340891
A
0.28
0.454
0.554
0.129
0.507
0.209
0.330
rs963468
115345577
A
0.38
0.809
0.777
0.902
0.608
0.609
0.580
rs3773678
115352768
A
0.06
0.780
0.855
0.487
0.770
0.972
0.556
rs2630351
115357749
A
0.03
0.954
0.144
0.168
0.999
0.811
0.211
rs167771
115358965
G
0.18
0.862
0.638
0.406
0.514
0.416
0.966
rs167770
115362252
G
0.31
0.260
0.911
0.298
0.694
0.593
0.982
rs226082
115363703
G
0.31
0.261
0.911
0.301
0.690
0.594
0.983
rs324029
115364313
A
0.31
0.259
0.913
0.296
0.722
0.593
0.964
rs10934256
115368342
A
0.17
0.229
0.898
0.478
0.246
0.147
0.669
Continued
6
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
Early environment, gender and genes in depression

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Table 2
Continued
Gene
Gene name
Chromosome
SNP
Position/
bp
Minor
allele
MAFz
P (G3EDev)
P (G3ESoc)
P (G3sex)
P (All)
P (rGEDev)
P (rGSoc)
rs1486009
115371222
G
0.12
0.721
0.667
0.745
0.571
0.387
0.600
rs6280
115373505
G
0.33
0.159
0.485
0.141
0.667
0.386
0.880
rs9825563
115382910
G
0.23
0.045yy
0.902
0.211
0.215
0.028
0.927
DRD4
Dopamine
receptor D4
11
rs3758653
626399
G
0.23
0.300
0.752
0.249
0.980
0.322
0.905
rs11246226
631191
A
0.49
0.749
0.748
0.166
0.925
0.908
0.097
DRD5
Dopamine
receptor D5
4
rs1878943
9375986
A
0.21
0.586
0.686
0.482
0.386
0.988
0.605
rs13106539
9406801
G
0.39
0.735
0.062
0.067
0.044{{{
0.532
0.384
The analyses were performed using PLINK’s linear and logistic regression models and interaction analysis. Empirical p values based on max(T) permutation are reported, with p values <0.05 shown
in bold.
*Defined by the presence of two out of three possible indicators for high early developmental risk: low birth weight, late motor development and late development of speech.
yDefined by the presence of two out of five possible indicators for high social risk environment: unwanted pregnancy, low socio-economic status, single parenthood, low level of education of mother
and low activity for information retrieval by the mother.
zMinor allele frequency.
xp¼0.0364 (b¼0.0414).
{p¼0.008 (b¼0.0440).
**p¼0.042 (b¼0.0320).
yyp¼0.022 (b¼e0.0396) in individuals at high risk group.
xxp>0.05 in both genders.
{{p¼0.0006 (b¼0.023) in males.
***b¼0.008.
yyyb¼0.012.
zzzb¼0.011.
xxxb¼0.022.
{{{b¼?0.
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
7
Early environment, gender and genes in depression

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a maximal amount of information on the nature of the
associations observed.
Haplotype analysis of COMT and DRD2 variants in relation
to the HSCL score
We performed 2-SNP and 3-SNP haplotype analyses
combining rs2239393 and rs4680 from COMT and their
neighbouringvariantsusing
approach. Evidence of association was observed for the
rs5993883ers2239393 haplotype CG spanning a region
from the space between LD blocks 1 and 2 to block 2 of
COMT (supplementary figure 1) (p¼0.0049, b¼0.055),
for the rs2239393ers4680 haplotype GG in block 2
(p¼0.0072, b¼0.044) and the rs5993883ers2239393e
rs4680 haplotype CGG (p¼0.0046, b¼0.055) in the high
early developmental risk group, in agreement with anal-
yses using single variants (table 3). As rs5993883 from the
haplotype had also given evidence of interaction with
gender (table 2), we further examined haplotype associ-
ation in males and females of the high-risk group sepa-
rately. We found that the haplotypes increased the risk for
depressive symptoms in males, but not in females
(p¼0.004, b¼0.083 for rs5993883ers2239393 haplotype
CG; p¼0.0037, b¼0.072 for rs2239393ers4680 haplotype
GG; and p¼0.0053, b¼0.083 for rs5993883ers2239393e
rs4680 haplotype CGG) (table 3). As is evident from the
b-values, each of the haplotypes accounts for more vari-
ance in depression than any individual constituent SNP.
Haplotype analysis of rs4274224 and rs4581480 from
DRD2, which gave evidence suggestive of an association
with the HSCL score in the complete sample, and of
their neighbouring variants, gave evidence of an associ-
ation of rs4648318ers4274224 haplotype GG spanning
from block 2 to block 3 of DRD2 (p¼0.0007, b¼0.041),
rs4274224ers4581480 haplotype
(p¼0.0069, b¼0.022), and rs4581480ers7131056 haplo-
type GA spanning from block 3 to block 4 (p¼0.0071,
b¼0.022) with the HSCL score. The 3-SNP haplotypes
rs4648318ers4274224ers4581480
(p¼0.0027,
rs7131056 haplotype GGA (p¼0.0081, b¼0.021) gave
evidence of an association in agreement with the find-
ings from the 2-SNP haplotypes as well as the single
variants (table 4). As one of the variants contained
within these haplotypes, namely rs4274224, also gave
evidence of interaction with gender as well as an associ-
ation with the HSCL score in males, we also examined
the association in males alone. The association signal
became stronger for all of the risk haplotypes, being
strongest forrs4648318ers4274224
(p¼0.00005, b¼0.069). Similarly as for the COMT
haplotypes, the b-values imply that each of the DRD2
haplotypes accounts for more variance in depression
than any individual constituent SNP.
theslidingwindow
GG in block3
haplotype
rs4274224ers4581480e
GGG
b¼0.032) and
haplotypeGG
Haplotype analysis of COMT and DRD2 variants in relation
to other neurobehavioural traits
Encouraged by the findings of the haplotype analyses, we
tested for associations of haplotypes rs5993883ers2239393
Table 3
Haplotype analysis of COMT variants on current depressive symptoms (Hopkins Symptom Check List score) in individuals at high early developmental risk group
(EDev)* from the NFBC 1966
Gene
Variant
Haplotype
Frequency
Males and females
at high risk EDev
Males at high
risk EDev
Females at high
risk EDev
b
p Value
b
p Value
b
p Value
COMT
2-SNP haplotype analysis
rs5993883ers2239393
CG
0.21
0.0552
0.0049
0.0828
0.0040
0.0216
0.4420
rs2239393ers4680
GG
0.32
0.0440
0.0072
0.0720
0.0037
0.0119
0.4914
AA
0.55
?0.0320
0.0428
?0.0411
0.0827
?0.0207
0.3370
rs4680ers4646316
GA
0.17
0.0434
0.0331
0.0624
0.0226
0.0206
0.3950
3-SNP haplotype analysis
rs5993883ers2239393ers4680
CGG
0.21
0.0548
0.0046
0.0826
0.0053
0.0211
0.4569
rs2239393ers4680ers4646316
GGA
0.17
0.0433
0.0344
0.0614
0.0258
0.0213
0.4311
Empirical p values based on permutation are reported, with p values <0.05 shown in bold.
*Defined by the presence of two out of three possible indicators for high early developmental risk: low birth weight, late motor development and late development of speech.
8
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Early environment, gender and genes in depression

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in COMT and rs4648318ers4274224 in DRD2, as well as
the single variant rs737866 in COMT with other traits
related to depression, including the HSCL depression and
anxiety subscales, depression diagnosis and TCI temper-
ament trait harm avoidance (table 5). In both genes, it is
evident that the association with HSCL stems mainly from
the subscale which reflects symptoms of depression and
not that reflecting anxiety (with HSCL depression
subscale, p¼0.018, b¼0.075 for COMT haplotype CG and
p¼0.0015, b¼0.060 for DRD2 haplotype GG; with HSCL
anxiety subscale, p¼0.288, b¼0.02 and p¼0.02 and
b¼0.033, respectively). We did not detect any evidence of
an association with depression diagnosis or with Harm
avoidance or its subcomponents.
DISCUSSION
We investigated genetic and environmental risk factors
for depression in a genetically isolated Finnish birth
cohort by assessing the relative impacts of mono-
aminergic candidate genes for depression in groups of
contrasting (high and low) early developmental and
social risk. We did not observe any robust genetic effects
of the analysed variants on depressiveness. However,
when measures of early development and social envi-
ronment were considered, some signals for association
were observed, although none of them survive correc-
tion for multiple testing. Our study sample provided
modest evidence of an interaction of COMT with the
measure of high early developmental risk, particularly in
males, and a contribution of an allelic variant of DRD2 to
genetic risk for depressiveness particularly in males
(table 2).
The COMT gene encoding for catechol-O-methyl-
transferase enzyme is among the most investigated genes
in psychiatric genetics. The enzyme degrades catechol-
amine neurotransmitters such as dopamine, norepi-
nephrine and epinephrine by catalysing the transfer of
a methyl group from S-adenosylmethionine to the cate-
cholamines. Its enzymatic activity varies according to a G-
to-A transition at codon 158 in the COMT gene, resulting
in a valine-to-methionine substitution (Val158Met) on
the protein level.31The enzyme encoded by the Val158
allele has a three- to four-fold higher activity than that
encoded by the Met158 allele. Here, we found an asso-
ciation of the haplotype comprising rs5993883 between
LD blocks 1 and 2 of COMT, as well as rs2239393 and
rs4680, which are two variants in virtually complete
linkage disequilbrium in block 2, with depressive symp-
toms in high-developmental-risk males (p¼0.0053). The
high-risk haplotype included the high-activity variant
Val158 of COMT, the allele G of rs4680. This allele has
repeatedly been found to be associated with a poor
response to pharmacological treatment of depres-
sion,32 33and a European multicentre study identified
an association between that allele and early-onset major
depression.34The Val158 allele has already been found
earlier to associate with cognitive deficits including poor
performance in tasks related to higher-order compo-
nents of processing35and perseverative errors, less effi-
cient physiological responses in the prefrontal cortex36
and even schizophrenia based on a meta-analysis,37
although the effect was not significant when studies with
allele frequencies deviating from the HardyeWeinberg
equilibrium were excluded.
In our study we observed evidence for an interaction
between COMT and a measure of early developmental
risk on depressive symptoms. This interaction could not
be explained through geneeenvironment correlations.
Nor were we able to detect a significant correlation of
the measure of early developmental risk with depressive
symptoms, despite prior evidence for the role of its
markers, which were low birth weight21 27and late motor
or verbal development,28in decreased psychiatric health
and well-being, including depression. This finding may
reflect the presence of other environmental risk indica-
tors which were not examined in our study. However,
they may also reflect individual variability in response to
the risk environment and presence of genetic factors
(such as the COMT haplotype containing Met158) that
may relate to resilience, adaptive changes in regulation
of emotion reactivity and successful coping with stress.38
The observed risk also seemed to arise from an aggre-
gation of the environmental indicators, as none of the
risk items separately gave evidence of G3E with the risk
Table 4
complete sample from the NFBC 1966
Haplotype analysis of DRD2 variants on current depressive symptoms (Hopkins Symptom Check List score) in the
GeneVariantHaplotype Frequency
Males and
females
Males
bb
p Valuep Value
DRD2 2-SNP haplotype analysis
rs4648318ers4274224
rs4274224ers4581480
GG
GG
AA
GA
0.05
0.07
0.48
0.07
0.0409
0.0220
0.0116
0.0220
0.0007
0.0069
0.0161
0.0071
0.0694
0.0321
?0.0237
0.0322
0.00005
0.0023
0.0004
0.0026rs4581480ers7131056
3-SNP haplotype analysis
rs4648318ers4274224ers4581480
rs4274224ers4581480ers7131056
GGG
GGA
0.05
0.07
0.0326
0.0215
0.0027
0.0081
0.0437
0.0317
0.0019
0.0033
Empirical p values based on permutation are reported, with p values <0.05 shown in bold.
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
9
Early environment, gender and genes in depression

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variants from COMT or DRD3 (data not shown). This
could reflect a cumulative nature of these environmental
influences, such that the effect of one marker may be
weak, but the accumulated effect of multiple markers,
together with genetic susceptibility, would be strong
enough to increase the risk for a deviant development of
emotional regulation and thus depressiveness.39There is
some prior evidence of interaction of COMT with a risk
environment on psychosis, antisocial behaviour and
dissociation. A study on children with ADHD showed
a geneeenvironment interaction between the Val/Val
genotype and low birth weight on early-onset antisocial
behaviour,40and the Val158 allele was also found to
associate with cannabis use and psychotic symptoms41
and with increasing levels of dissociation in those
exposed to higher levels of childhood trauma.42Inter-
estingly, a recent report43revealed an impact of that
polymorphism on gender-related patterns of regulation
of emotions (activation in limbic and paralimbic
regions) in line with findings of the present study.
Another main finding of the present study, and statis-
tically the strongest one, was observed in the dopamine
receptor D2 gene DRD2, where a haplotype comprising
the intronic variants rs4648318 in LD block 2 and
rs4274224 in block 3 was found to associate with depres-
sive symptoms particularly in males, regardless of their
early environment (p¼0.00005). Dopamine receptors
have key roles in a variety of processes in the vertebrate
central nervous system, and dysfunction in dopaminergic
neurotransmission may therefore predispose to a variety
of neuropsychiatric disorders. Among the receptor genes,
DRD2 has attracted the most attention and has been
implied to have a role in the aetiology of several psychi-
atric disorders. However, there are only a few previous
reports on unipolar depression, including positive,44
nominal45and negative46 47findings, and for results on
depression conditional on risk environment.44 46 48
Our varying results for males and females in general
imply different mechanisms of mood regulation and
possible gender-specific responses to environmental
effectors. Gender differences in depression2 49as well as
in temperament traits49have previously been reported in
various populations, including the current one,50and
the prevalence of depression is higher in women.51A
true gender-specific effect of genetic variants on
depressiveness would not be surprising, as there is
evidence of gender differences in dopaminergic func-
tion52that may be oestrogen-dependent.
It is noteworthy that despite previous reports of the
5-HTTLPR variant,13we did not detect any evidence of
an association for SLC6A4. Similarly, a recent meta-
analysis did not find any evidence of an association with
depression alone, or in interaction with stressful life
events,16although a current review14and a meta-analysis
of all studies to date15support the positive association
findings and the role of 5-HTTLPR and stress in
depression. The SLC6A4 SNPs included in our study tag
the 5-HTTLPR well (D9>0.9), as determined using
Table 5
Haplotype analysis of COMT and DRD2 variants on other neurobehavioural traits in the NFBC1966
Gene
Variant
Group
Gender
HSCL (total)
HSCL
(depression)
HSCL (anxiety)
Depression
diagnosis
Harm avoidance
b
p Value
b
p Value
b
p Value
OR
p Value
b
p Value
COMT
rs737866
High risk
Males
0.0640
0.0254
0.0440
0.2239
0.0150
0.6157
0.7130
0.5004
0.7820
0.3799
rs5993883-rs2239393 (CG)
High risk
Males
0.0830
0.0040
0.0750
0.0176
0.0200
0.2877
0.2100
0.1506
1.2040
0.1433
DRD2
rs4648318- rs4274224 (GG)
All
Males
0.0694
0.00005
0.0600
0.0015
0.0326
0.0212
0.8280
0.6798
1.0430
0.07009
Empirical p values based on permutation are reported, with p values <0.05 shown in bold.
HSCL, Hopkins Symptom Check List.
10
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Early environment, gender and genes in depression

Page 11

genotypes from a population-based Finnish Health 2000
study.53Moreover, the LD measure thus obtained is
conservative, since in the population under current
study, LD has been shown to be stronger than in the
general Finnish population, which was represented by
the Health 2000 study sample.54
We did not use the Bonferroni correction for multiple
testing, owing to limitations of sample size and expected
magnitude of gene effects in complex traits. Although
none of the results from the primary analyses (table 2)
surviveconservative correction,
a priori hypothesis based on previously published studies
supports the validity of our most robust findings. It is,
however, noteworthy that they were observed only when
the sample was conditioned on measures of early devel-
opment or of social environment, or gender. Still, the
strongest association signal, obtained using DRD29s
rs4274224 with HSCL score in males (p¼0.0006),
remains close to statistical significance, even when taking
into account the amount of multiple testing performed.
The finding was further supported by results of our
haplotype analysis containing rs4274224, which showed
a statistically significant association with the HSCL score
in males (p¼0.00005).
There are some limitations in the present study. First,
it is notable that depression as defined here did not
necessarily signify a clinical diagnosis of major depres-
sion. Instead, it was defined based either on self-report
or on the score from HSCL, which as a measure has its
limitations. However, the prevalence of depressed mood
was in the same range as in earlier reports.1 55Second,
there was a notable drop-out rate among the original
material of all cohort members. About half of the orig-
inal cohort members did not participate in this study.
Finally, when the NFBC 1966 study was initiated, it was
not possible to predict that an investigation such as the
present one would one day be conducted. Therefore, we
are limited by the original choice of variables to be
collected, and the measures of early development or of
social environment may only be indicators or markers of
risk rather than risk factors themselves.39It is also
noteworthy that we did not detect any association of our
measure of current depression with the measure of high
early developmental risk, despite it being formulated
based on previous reports of their effects on psychiatric
health and well-being.27e30
genetic risk may be modulated by early life stress, even
though the direct link between early life environment
and current status would be too weak to be detected in
our study sample, and this modulating effect may be
seen in the results of the G3E analysis.
The current study has several potential advantages,
such as the availability of longitudinal follow-up data
starting antenatally, enabling us to include the environ-
mental dimension without any risk of recall bias.
Another advantage is the unique genetic structure of our
study cohort, characterised by isolation, founder effect,
multiple bottlenecks and more genetic homogeneity
a neurobiological
However, the effect of
compared with many other isolates,56allowing us to
identify genetic risk loci that may be missed in the
screening of other more heterogeneous populations.
Furthermore, the subjects were representative, with all
cohort members born in the same year and within
a geographically defined area.
In addition, the size of the sample is sufficient to
identify genetic variants of moderate impact. We also
have both genders represented in almost equal amounts
(48% males, 52% females), which is notable since
gender differences are evident both in depression2 49
and in temperament traitsdfor example, harm avoid-
ance.49Furthermore, it is beneficial that the sample is
a 1-year birth cohort, as it is well established that some
psychiatric traits, such as harm avoidance57of tempera-
ment, are age-dependent. We can therefore isolate
genetic effects from the effects of ageing.
Our results support a modest role of COMTand DRD2,
two genes of monoamine neurotransmission, in the
aetiology of depression conditional on environmental
risk, particularly in males, though not direct effects of
monoaminergic genes in this unselected population.
These findings imply that the nature of the role of
monoaminergic genes in depression should be exam-
ined further in future studies, and pending replication
in other, independent population samples.
Author affiliations
1Public Health Genomics Unit, Institute for Molecular Medicine Finland FIMM,
University of Helsinki and National Institute for Health and Welfare, Helsinki,
Finland
2National Institute for Health and Welfare, Helsinki, Finland
3Department of Medical Genetics, University of Helsinki, Helsinki, Finland
4Department of Psychiatry, Helsinki University Central Hospital, Helsinki,
Finland
5Department of Psychiatry, University of Oulu and Oulu University Hospital,
Oulu, Finland
6Academy of Finland, Helsinki, Finland
7Tampere School of Public Health, University of Tampere, Tampere, Finland
8Department of Psychiatry, Tampere University Hospital, Tampere, Finland
9Institute of Health Sciences, University of Oulu, Oulu, Finland
10Department of Epidemiology and Public Health, Imperial College, London,
UK
11Department of Child and Adolescent Health, National Public Health Institute,
Helsinki, Finland
12Semel Institute for Neuroscience and Human Behavior, University of
California, Los Angeles, California, USA
13Program in Medical and Population Genetics, The Broad Institute of MIT and
Harvard, Cambridge, Massachusetts, USA
14Wellcome Trust Sanger Institute, Cambridge, UK
Funding This study was funded by the Academy of Finland’s CoE in Complex
Disease Genetics; the Biocentrum Helsinki Foundation; the Academy of
Finland’s grant to the NFBC Studies to TP, Post-doctoral Fellowship to AL and
Academy Researcher Fellowship to JM; the University of Helsinki Research
Foundation grant for young researchers to ESN; and the Signe and Ane
Gyllenberg Foundation grant to PM.
Competing interests None.
Patient consent Obtained.
Ethics approval Ethics approval was provided by the Ethical Committee of
Oulu University Faculty of Medicine.
Nyman ES, Sulkava S, Soronen P, et al. BMJ Open 2011;1:e000087. doi:10.1136/bmjopen-2011-000087
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Contributors TP, ESN, SS, JM, M-RJ, JV, NF, PM, LP and M-RJ designed the
study and wrote the protocol. ESN and, to some extent, TP also managed the
literature searches. SS and ESN undertook the statistical analyses. ESN and TP
wrote the first draft of the manuscript, and all authors contributed to its later
versions. All authors contributed to and have approved the final manuscript.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement Additional data on this study available from the
corresponding author at tiina.paunio@thl.fi.
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